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All Technical Committee Conferences (Searched in: All Years)
| Committee | Date Time | Place | Paper Title / Authors | Abstract | Paper # | |
| MI | 2024-03-04 10:46 |
Okinawa | OKINAWAKEN SEINENKAIKAN (Primary: On-site, Secondary: Online) |
Automated musculoskeletal segmentation of torso CT images Sanaa Amina Gourine, Mazen Soufi, Yoshito Otake (NAIST), Yuto Masaki (NAIST-PSP Corporation), Yoko Murakami, Yukihiro Nagatani, Yoshiyuki Watanabe (Shiga Univ), Keisuke Uemura (Osaka Univ), Masaki Takao (Ehime Univ), Nobuhiko Sugano (Osaka Univ), Yoshinobu Sato (NAIST)  MI2023-70 |
Musculoskeletal segmentation (MSK) in CT is helpful for several applications, including body composition analysis, biome... [more] | MI2023-70 pp.122-126 |
| IBISML | 2023-12-21 10:55 |
Tokyo | National Institute of Informatics (Primary: On-site, Secondary: Online) |
On the benefits of Partial Stochastic Bayesian Neural Networks Koki Sato, Daniel Andrade (Hiroshima Univ.) IBISML2023-36 |
Bayesian neural networks (BNNs) can model uncertainty in the prediction results better than ordinary neural networks. Ho... [more] | IBISML2023-36 pp.37-41 |
| NC, IBISML, IPSJ-BIO, IPSJ-MPS [detail] | 2022-06-27 14:25 |
Okinawa | (Primary: On-site, Secondary: Online) |
A Bagging Method to Improve the Accuracy of Gaussian Process Regression for Neural Architecture Search Rion Hada, Masao Okita, Fumihiko Ino (Osaka Univ.) NC2022-2 IBISML2022-2 |
The goal of this study is to improve performance estimation for neural network architectures in neural architecture sear... [more] | NC2022-2 IBISML2022-2 pp.6-13 |
| RECONF | 2021-09-10 15:00 |
Online | Online | Parallel Calculation of Local Scores in Bayesian Network Structure Learning using FPGA Ryota Miyagi (Kyoto Univ.), Hideki Takase (U. Tokyo/JST) RECONF2021-22 |
Bayesian network (BN) is a directed acyclic graph that represents relationships among variables in data sets. Because le... [more] | RECONF2021-22 pp.30-35 |
| MI | 2021-03-15 15:30 |
Online | Online | Evaluation of Bayesian Active Learning for Segmentation of Liver and Spleen in Large Scale Abdominal MR Data Sets Bin Zhang, Yoshito Otake, Mazen Soufi (NAIST), Masatoshi Hori (Kobe University), Noriyuki Tomiyama (Osaka University), Yoshinobu Sato (NAIST) MI2020-60 |
Manual annotation in image segmentation is time-consuming and expensive. In order to obtain large number of annotated da... [more] | MI2020-60 pp.62-65 |
| MI, IE, SIP, BioX, ITE-IST, ITE-ME [detail] | 2020-05-28 12:40 |
Online | Online | [Special Talk]
Generalization of coherent point drift and its acceleration Osamu Hirose (Kanazawa Univ.) SIP2020-1 BioX2020-1 IE2020-1 MI2020-1 |
Point set registration is to find point-to-point correspondences between point sets, each of which represents the shape ... [more] | SIP2020-1 BioX2020-1 IE2020-1 MI2020-1 pp.1-3 |
| R | 2019-12-13 14:25 |
Tokyo | Kikai-Shinko-Kaikan Bldg. | Statistical method of estimating the date when school lunch caused mass food poisoning was supplied Mitsuhiro Kimura (Hosei Univ.), Shuhei Ota (Kanagawa Univ.) R2019-51 |
We focus on estimating the date when school lunch caused mass food poisoning was supplied. In the literature, a log-norm... [more] | R2019-51 pp.7-12 |
| ISEC, SITE, ICSS, EMM, HWS, BioX, IPSJ-CSEC, IPSJ-SPT [detail] | 2019-07-24 10:55 |
Kochi | Kochi University of Technology | Stochastic Existence Connecting Logos that are not necessarily completely divided and Language Games
-- Limitations of Security Models and the Possibility of Artificial Intelligence -- Tetsuya Morizumi (KU) ISEC2019-49 SITE2019-43 BioX2019-41 HWS2019-44 ICSS2019-47 EMM2019-52 |
In this paper we describe that AI architecture including input data in artificial intelligence system for Bayesian estim... [more] | ISEC2019-49 SITE2019-43 BioX2019-41 HWS2019-44 ICSS2019-47 EMM2019-52 pp.317-324 |
| NS, IN (Joint) |
2017-03-03 11:40 |
Okinawa | OKINAWA ZANPAMISAKI ROYAL HOTEL | Reconstruction of Virtual Network by Bayesian Attractor Model Tatsuya Otoshi, Yuichi Ohshita, Masayuki Murata (Osaka Univ.) IN2016-129 |
Network Virtualization is expected to handle the various network traffic induced by such as IoT applications because a v... [more] | IN2016-129 pp.193-198 |
| ICSS | 2014-11-28 11:10 |
Miyagi | Tohoku Gakuin University (Tagajo Campus) | searching malicious URL from vast webspace Bo Sun (Waseda Univ.), Mitsuaki Akiyama, Takeshi Yagi (NTT), Tatsuya Mori (Waseda Univ.) ICSS2014-61 |
Many Web-based attacks such as Drive-by-download and phishing scam are easily triggered by accessing landing page URL.... [more] |
ICSS2014-61 pp.61-66 |
| IBISML | 2013-11-12 15:45 |
Tokyo | Tokyo Institute of Technology, Kuramae-Kaikan | [Poster Presentation]
Performance Comparisons between Dependency Networks and Bayesian Networks Kazuya Takabatake, Shotaro Akaho (AIST) IBISML2013-41 |
Dependency networks are graphical models in which tasks of learning are done by totally local and simple algorithms of i... [more] | IBISML2013-41 pp.39-44 |
| IBISML | 2011-11-09 15:45 |
Nara | Nara Womens Univ. | An Extension of Probabilistic PCA for Correlated Samples Kohei Hayashi (NAIST), Masanori Kawakita (Kyushu Univ), Kazushi Ikeda (NAIST) IBISML2011-50 |
Principal component analysis (PCA) is one of dimensional reduction methods and has widely been used for feature extracti... [more] | IBISML2011-50 pp.57-60 |
| IBISML | 2011-11-10 15:45 |
Nara | Nara Womens Univ. | Sequential Network Change Detection with Its Applications to Advertisement Impact Relation Analysis Yu Hayashi, Kenji Yamanishi (Univ. of Tokyo.) IBISML2011-71 |
This paper addresses the issue of network change detection from non-stationary time series data. We employ as a represen... [more] | IBISML2011-71 pp.199-206 |
| IBISML | 2011-06-20 14:30 |
Tokyo | Takeda Hall | Network Change Detection with Its Applications to Advertisement Impact Relation Analysis Yu Hayashi, Kenji Yamanishi (Univ. of Tokyo.) IBISML2011-9 |
This paper addresses the issue of network change detection with its applications to advertisement impact relation analys... [more] | IBISML2011-9 pp.59-66 |
| MBE | 2010-10-14 14:45 |
Osaka | Osaka Electro-Communication University | Sequential Error Rate Evaluation of EEG:SSVEP Binary Classification Problem
-- Bayesian Sequential Learning with Sequential Monte Carlo method -- Hideyuki Hara (Waseda Univ.), Atsushi Takemoto (Kyoto Univ.), Yumi Dobashi (Waseda Univ.), Katsuki Nakamura (Kyoto Univ.), Takashi Matsumoto (Waseda Univ.) MBE2010-31 |
An attempt was made to evaluate the \textit{Sequential Error Rate} (SER) of an SSVEP classification problem with a Bayes... [more] | MBE2010-31 pp.17-22 |
| USN, IPSJ-UBI | 2009-07-16 14:30 |
Kyoto | ATR (Kyoto) | Applying a Probabilistic Inference Stream Processing Engine to a Camera Sensor Network Ryo Sato, Hideyuki Kawashima, Hiroyuki Kitagawa (Univ. of Tsukuba) USN2009-20 |
The purpose of this paper is to appropriately incorporate Bayesian networks into a relational stream processing system ... [more] |
USN2009-20 pp.69-74 |
| PRMU, NLC, TL | 2006-10-20 16:15 |
Tokyo | Lawn weeds detection methods using image processing techniques Ukrit Watchareeruetai, Yoshinori Takeuchi, Tetsuya Matsumoto, Hiroaki Kudo, Noboru Ohnishi (Nagoya Univ.) |
In this work, three methods of lawn weeds detection based on various image processing techniques, Bayesian classifier, m... [more] | PRMU2006-115 pp.65-70 |
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